@ewindisch @IOpipes The Truth Behind Serverless CTO & Co-founder, IOpipe Erica Windisch
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@ewindisch @IOpipes
The Truth Behind Serverless
CTO & Co-founder, IOpipe
Erica Windisch
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What-a-less?
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ServerlessCultureDon’t build, when you can buy. Build as little as necessary.
Build with the minimum operational complexity.
Maybe all you need are some circles
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The 12 Factor AppI. Codebase One codebase tracked in revision control, many deploys II. Dependencies Explicitly declare and isolate dependencies III. Config Store config in the environment IV. Backing services Treat backing services as attached resources V. Build, release, run Strictly separate build and run stages VI. Processes Execute the app as one or more stateless processes
VII. Port binding Export services via port binding VIII. Concurrency Scale out via the process model IX. Disposability Maximize robustness with fast startup and graceful shutdown X. Dev/prod parity Keep development, staging, and production as similar as possible XI. Logs Treat logs as event streams XII. Admin processes Run admin/management tasks as one-off processes
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Amazon’s “Serverless (functions) Manifesto”✤ Function are the unit of deployment and scaling. ✤ No machines, VMs, or containers visible in the programming model. ✤ Permanent storage lives elsewhere. ✤ Scales per request; Users cannot over- or under-provision capacity. ✤ Never pay for idle (no cold servers/containers or their costs). ✤ Implicitly fault-tolerant because functions can run anywhere. ✤ BYOC - Bring Your Own Code. ✤ Metrics and logging are a universal right.
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Platforms- AWS Lambda - Azure Functions - Google Cloud
Functions - Oracle’s fn() - IBM Bluemix
Functions - OpenWhisk - Spring Functions
- Galactic Fog - Stdlib - Now.sh - Auth0 Webtasks &
Extend - AppEngine Classic - Heroku - Parse - Firebase
- Google PubSub - Google BigQuery - AWS S3 - AWS SNS - AWS Athena - AWS Kinesis - AWS DynamoDB & more
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Platforms - FaaS providers- AWS Lambda - Azure Functions - Google Cloud
Functions - Oracle’s fn() - IBM Bluemix
Functions - OpenWhisk - Spring Functions
- Galactic Fog - Stdlib - Now.sh - Auth0 Webtasks &
Extend - AppEngine Classic - Heroku - Parse - Firebase
- Google PubSub - Google BigQuery - AWS S3 - AWS SNS - AWS Athena - AWS Kinesis - AWS DynamoDB & more
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Platforms - Event sources- AWS Lambda - Azure Functions - Google Cloud
Functions - Oracle’s fn() - IBM Bluemix
Functions - OpenWhisk - Spring Functions
- Galactic Fog - Stdlib - Now.sh - Auth0 Webtasks &
Extend - AppEngine Classic - Heroku - Parse - Firebase
- Google PubSub - Google BigQuery - AWS S3 - AWS SNS - AWS Athena - AWS Kinesis - AWS DynamoDB & more
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75 GB storage limit for all functions
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5 minute maximum duration
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~20ms for “hello world”
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128MB to 1.5GB memory
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1000 containers max (by default)
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Functions lazy-loaded from s3
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Containers + processes long-lived, automatically scaled and garbage-collected.
4.5 minutes to 4.5 hours
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Pauses / unpauses containers between events
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non-root user
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/ read-only /tmp 512MB max
function mounted to /var/task
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Amazon’s “Serverless (functions) Manifesto”✤ Function are the unit of deployment and scaling. ✤ No machines, VMs, or containers visible in the programming model. ✤ Permanent storage lives elsewhere. ✤ Scales per request; Users cannot over- or under-provision capacity. ✤ Never pay for idle (no cold servers/containers or their costs). ✤ Implicitly fault-tolerant because functions can run anywhere. ✤ BYOC - Bring Your Own Code. ✤ Metrics and logging are a universal right.
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Demo Slide
Click to add text
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App CreationUpload to S3
CreateFunction API call pointing to S3 resource
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WarmingAmazon automatically scales VMs & allocates to users. They do not warm processes/containers
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Triggers & Events- Invoke functions via API
- Configure event source to function mappings
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ScheduleEvents are mapped to running containers first,
Or new containers are spawned to process events.
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InvokeSynchronous HTTP API Container is spawned, if not existing.
Existing container is unpaused, fed event, then paused.
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VisibilityLogs and metrics are sent to Cloudwatch.
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Garbage Collection- Reap containers when they're no longer active
- Reap VMs when they’re no longer active
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Orchestration Challenges
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Scaling VMs and scaling containers
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Each tenant needs a container cluster?
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Are Kubernetes or Swarm fast enough?
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HTTP + serialization/deserializationfor series of events are SLOW
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Implementation Details
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How to minimize latency of API processing & response?
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how do we do messaging / communication?
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How do we manage state?
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How do we orchestrate containers?
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Which language?
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Putting it back togetherhttps://prezi.com/view/K5Xz8xT6BoTYbx2EgGk1/
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Finally…
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Remember…
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It’s all about the events.
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Events are always immutable.
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Event processing can and should be immutable.
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Event processing should be fast & low-latency.
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Events generate events.(it’s turtles all the way down)
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FaaS architecture should be designed for performance and immutability
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Don’t build when you can buy(you probably shouldn’t build anything I just showed you!)
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